Meeting Job-Level Dependencies by Task Merging
Industrial applications are often time critical and subject to end-to-end latency constraints. Job-level dependencies can be leveraged to specify a partial ordering on tasks' jobs already at early design phases, agnostic of the hardware platform or scheduling algorithm, and guarantee that end-t...
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| Vydáno v: | Proceedings of the ASP-DAC ... Asia and South Pacific Design Automation Conference s. 792 - 798 |
|---|---|
| Hlavní autor: | |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
22.01.2024
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| Témata: | |
| ISSN: | 2153-697X |
| On-line přístup: | Získat plný text |
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| Abstract | Industrial applications are often time critical and subject to end-to-end latency constraints. Job-level dependencies can be leveraged to specify a partial ordering on tasks' jobs already at early design phases, agnostic of the hardware platform or scheduling algorithm, and guarantee that end-to-end latency constraints of task chains are met as long as the job-level dependencies are respected. However, their realization at runtime can introduce overheads and complicates the scheduling and timing analysis. This work presents an approach that merges multi-periodic tasks that are connected by job-level dependencies to a single task. A Constraint Programming formulation is presented that optimally merges such task clusters while all job-level dependencies are respected. Such an approach removes the need to consider job-level dependencies at runtime without being bound to a specific scheduling algorithm. Evaluations highlight the applicability of the approach by system-level experiments and showcase the scalability of the approach using synthetic task clusters. |
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| AbstractList | Industrial applications are often time critical and subject to end-to-end latency constraints. Job-level dependencies can be leveraged to specify a partial ordering on tasks' jobs already at early design phases, agnostic of the hardware platform or scheduling algorithm, and guarantee that end-to-end latency constraints of task chains are met as long as the job-level dependencies are respected. However, their realization at runtime can introduce overheads and complicates the scheduling and timing analysis. This work presents an approach that merges multi-periodic tasks that are connected by job-level dependencies to a single task. A Constraint Programming formulation is presented that optimally merges such task clusters while all job-level dependencies are respected. Such an approach removes the need to consider job-level dependencies at runtime without being bound to a specific scheduling algorithm. Evaluations highlight the applicability of the approach by system-level experiments and showcase the scalability of the approach using synthetic task clusters. |
| Author | Becker, Matthias |
| Author_xml | – sequence: 1 givenname: Matthias surname: Becker fullname: Becker, Matthias email: mabecker@kth.se organization: KTH Royal Institute of Technology,Sweden |
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| PublicationTitle | Proceedings of the ASP-DAC ... Asia and South Pacific Design Automation Conference |
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| Snippet | Industrial applications are often time critical and subject to end-to-end latency constraints. Job-level dependencies can be leveraged to specify a partial... |
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| SubjectTerms | Constraint handling Design automation Job shop scheduling Merging Runtime Scalability Scheduling algorithms |
| Title | Meeting Job-Level Dependencies by Task Merging |
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